How are the two report completion-time arrays generated in NumPy?

Conditions

• Use the uniform model introduced earlier.
• `sims` must already be defined.

Reasoning, step by step

1. Set the number of simulation runs to one million with `sims = 1000000`.
2. Generate one million random completion times for report A from the interval 1 to 5 hours using `A = np.random.uniform(1, 5, sims)`.
3. Generate one million random completion times for report B from the interval 2 to 6 hours using `B = np.random.uniform(2, 6, sims)`.
4. Compute the total completion time for each paired simulation run by adding A and B using `duration = $A + B$`.

Example

The code lines visible are `A = np.random.uniform(1, 5, sims)` and `B = np.random.uniform(2, 6, sims)`. The narrator states, "they will take anywhere between 1 to 5 hours and 2 to 6 hours to complete, so let's define those values for the arguments for these functions."

Common misconceptions

• Assuming the arrays are generated with a normal distribution instead of a uniform distribution.
• Forgetting that the third argument in `np.random.uniform` specifies the number of samples to generate.

Watch the explanation

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